Sensor data prioritization for autonomous vehicle based on vehicle operation data

ABSTRACT

An autonomous vehicle includes a control system, an array of sensors, processing logic, and a switch. The processing logic generates operation instructions based on sensor data and the control system controls the autonomous vehicle based on the operation instructions. The array of sensors generate the sensor data that is related to objects in an external environment. The switch is coupled between the sensors and the processing logic to buffer the processing logic from the sensor data. The switch is further coupled between the processing logic and the control system to provide the operation instructions from the processing logic to the control system. The switch includes a prioritization engine that prioritizes an order of transmission, from the switch to the processing logic, of the first sensor data over the second sensor data based on received vehicle operation data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Non-Provisional ApplicationNo. 16/588,996 filed Sep. 30, 2019, which is hereby incorporated byreference in its entirety.

TECHNICAL FIELD

This disclosure relates generally to autonomous vehicles and inparticular to sensor data prioritization for autonomous vehicles.

BACKGROUND INFORMATION

The automobile industry is currently developing autonomous features forcontrolling vehicles under certain circumstances. According to SAEInternational standard J3016, there are 6 levels of autonomy rangingfrom Level 0 (no autonomy) up to Level 5 (vehicle capable of operationwithout operator input in all conditions). A vehicle with autonomousfeatures utilizes sensors to sense the environment that the vehiclenavigates through. Acquiring and processing data from the sensors allowsthe vehicle to safely navigate through its environment.

BRIEF SUMMARY OF THE INVENTION

In an implementation of the disclosure, an autonomous vehicle includesan array of sensors, processing logic, and a switch such as a timesensitive network switch. The array of sensors is configured to captureone or more objects in an external environment of the autonomous vehicleand generate sensor data related to the external environment. Theprocessing logic is configured to receive the sensor data and generatean external environment representation based on the sensor data. Theswitch is configured to receive the sensor data from the array ofsensors. The switch may include a prioritization engine and an outputcommunication port. The prioritization engine is configured toprioritize a transmission of first sensor data from a first sensor groupof the array of sensors over transmission of second sensor data from asecond sensor group of the array of sensors. The first sensor data andthe second sensor data are prioritized, in time, based on vehicleoperation data received by the prioritization engine. The outputcommunication port is configured to transmit the first sensor data tothe processing logic prior to sending the second sensor data.

In an implementation, the array of sensors includes rear sensorsdisposed to detect or image a rear-ward area of the autonomous vehicleand front sensors disposed to detect or image a frontside area of theautonomous vehicle and the vehicle operation data indicates a rear-warddirection of the autonomous vehicle. The first sensor data is generatedby the rear sensors and the second sensor data is generated by the frontsensors. The switch may include an input port configured to receive thevehicle operation data from a vehicle bus of the autonomous vehicle andthe vehicle operation data may include a reverse transmission state.

In an implementation, the array of sensors includes rear sensorsdisposed to detect or image a rear-ward area of the autonomous vehicleand front sensors disposed to detect or image a frontside area of theautonomous vehicle and the vehicle operation data indicates a forwarddirection of the autonomous vehicle. The first sensor data may begenerated by the front sensors and the second sensor data is generatedby the rear sensors. The switch may include an input port configured toreceive the vehicle operation data from a vehicle bus of the autonomousvehicle and the vehicle operation data includes a forward-geartransmission state.

The vehicle operation data includes a speed of the autonomous vehicle,in some implementations. The array of sensors includes at least one of aLight Detection and Ranging (LIDAR) sensor, an ultrasonic sensor, acamera, or a Radar Detection and Ranging (RADAR) sensor, in someimplementations.

In an implementation of the disclosure, a method of prioritizing datatransfer in an autonomous vehicle includes receiving sensor data from anarray of sensors configured to capture one or more objects of anexternal environment of the autonomous vehicle and receiving vehicleoperation data representative of a vehicle state of the autonomousvehicle. The method also includes selecting a first sensor group of thearray of sensors of the autonomous vehicle based on the vehicleoperation data and based on selecting the first sensor group,prioritizing, by a switch, transmission of first sensor data from thefirst sensor group over transmission of second sensor data from a secondsensor group of the array of sensors where the second sensor group isdifferent from the first sensor group. In some implementations, theprocessing logic selects the first sensor group.

In an implementation, the transmission of the first sensor data and thesecond sensor data is from the switch to processing logic of theautonomous vehicle and the switch is configured to receive the firstsensor data and the second sensor data from the array of sensors. Themethod may further include generating, with the processing logic, anexternal environment representation of the autonomous vehicle with thefirst sensor data and without the second sensor data. The method mayalso further include generating an updated external environmentrepresentation of the autonomous vehicle with the second sensor data andthe updated external environment representation of the autonomousvehicle is generated subsequently to the external environmentrepresentation.

The vehicle state indicates a transmission gear of a transmission of theautonomous vehicle, in some implementations. The vehicle operation datamay be received from a vehicle data bus of the autonomous vehicle.

In some implementations, the array of sensors includes rear sensorsdisposed to detect or image a rear-ward area of the autonomous vehicleand front sensors disposed to detect or image a frontside area of theautonomous vehicle. The vehicle operation data may indicate a rear-warddirection of the autonomous vehicle. The first sensor data may begenerated by the rear sensors and the second sensor data may begenerated by the front sensors.

In some implementations, the array of sensors includes rear sensorsdisposed to detect or image a rear-ward area of the autonomous vehicleand front sensors disposed to detect or image a frontside area of theautonomous vehicle and the vehicle operation data may indicate a forwarddirection of the autonomous vehicle. The first sensor data may begenerated by the front sensors and the second sensor data may begenerated by the rear sensors.

The vehicle operation data includes a speed of the autonomous vehicle,in some implementations. The array of sensors includes at least one of aLIDAR sensor or a RADAR sensor, in some implementations.

In an implementation of the disclosure, an autonomous vehicle includesprocessing logic, and a switch such as a time sensitive network switch.The processing logic is configured to receive sensor data and generatean external environment representation based on the sensor data and thesensor data is received from an array of sensors configured to captureone or more objects in an external environment of the autonomousvehicle. The switch is configured to receive the sensor data from thearray of sensors and the switch is configured to prioritize atransmission of first sensor data from a first sensor group of the arrayof sensors over transmission of second sensor data from a second sensorgroup of the array of sensors. The first sensor data and the secondsensor data are prioritized, in time, based on vehicle operation datareceived by the switch.

In an implementation, the switch includes an input port configured toreceive the vehicle operation data from a vehicle bus of the autonomousvehicle. In one implementation the vehicle operation data includes aspeed of the autonomous vehicle.

In one illustrative implementation an autonomous vehicle traverses inrearward direction. To travel in rearward direction, the autonomousvehicle may enter a reverse transmission state where the transmission ofthe vehicle is in reverse. The reverse transmission state may bedigitally incorporated into a vehicle operation data packet sent to atime sensitive network switch. When the autonomous vehicle is traversingin the rearward direction, certain sensors in the array of sensors onthe autonomous vehicle may be better positioned to detect or image abicycle or pedestrian behind the vehicle and detecting or imaging therear of the vehicle may have a higher priority. Hence rear-facingsensors from the array of sensors may be selected based on vehicleoperation data that includes a reverse transmission state that indicatesa transmission of the vehicle is shifted into reverse. Based onselecting the rear-facing sensors, the switch may prioritize thetransmission of the sensor data generated by the rear-facing sensors.Therefore, sensor data from sensors that are better positioned to detector image particular objects may be prioritized for transmission and/orprocessing so that the autonomous vehicle has faster access to datacorresponding to particular objects that have greater impact onimmediate navigation of the autonomous vehicle.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive implementations of the invention aredescribed with reference to the following figures, wherein likereference numerals refer to like parts throughout the various viewsunless otherwise specified.

FIG. 1A illustrates an autonomous vehicle including an array of examplesensors, in accordance with aspects of the disclosure.

FIG. 1B illustrates a top view of an autonomous vehicle including anarray of example sensors, in accordance with aspects of the disclosure.

FIG. 1C illustrates an example vehicle control system including sensors,a drivetrain, and a control system, in accordance with aspects of thedisclosure.

FIG. 2 illustrates a block diagram of an example system that may beincluded in a vehicle, in accordance with aspects of the disclosure.

FIG. 3 illustrates an autonomous vehicle navigating a roadway, inaccordance with aspects of the disclosure.

FIG. 4 illustrates a flow chart with an example process of prioritizingsensor data based on vehicle operation data, in accordance with aspectsof the disclosure.

FIG. 5 illustrates various sensors and a field-of-imaging of sensors ofan autonomous vehicle, in accordance with aspects of the disclosure.

FIG. 6 illustrates an autonomous vehicle travelling in a forwarddirection on a roadway, in accordance with aspects of the disclosure.

DETAILED DESCRIPTION

Implementations of an autonomous vehicle and a system for an autonomousvehicle are described herein. In the following description, numerousspecific details are set forth to provide a thorough understanding ofthe implementations. One skilled in the relevant art will recognize,however, that the techniques described herein can be practiced withoutone or more of the specific details, or with other methods, components,or materials. In other instances, well-known structures, materials, oroperations are not shown or described in detail to avoid obscuringcertain aspects.

Reference throughout this specification to “one implementation” or “animplementation” means that a particular feature, structure, orcharacteristic described in connection with the implementation isincluded in at least one implementation of the present invention. Thus,the appearances of the phrases “in one implementation” or “in animplementation” in various places throughout this specification are notnecessarily all referring to the same implementation. Furthermore, theparticular features, structures, or characteristics may be combined inany suitable manner in one or more implementations.

Throughout this specification, several terms of art are used. Theseterms are to take on their ordinary meaning in the art from which theycome, unless specifically defined herein or the context of their usewould clearly suggest otherwise. For the purposes of this disclosure,the term “autonomous vehicle” includes vehicles with autonomous featuresat any level of autonomy of the SAE International standard J3016.

This disclosure includes implementations of an autonomous vehicleincluding a plurality of sensors and prioritizing sensor data based onvehicle operations data of the autonomous vehicle. Example sensors thatmay be used in autonomous vehicles includes camera systems, RadioDetection and Ranging (RADAR) systems, (Light Detection and Ranging)LIDAR systems, 3D positioning sensors including Global PositioningSystem (GPS), ultrasonic sensors, and Inertial Measurement Units (IMU).The sensors may be positioned in different locations of the autonomousvehicle and different sensor modalities may be better configured tosense or detect or image objects depending on the speed, direction,and/or transmission-gear of the autonomous vehicle, for example.

In implementations of the disclosure, sensor data from an array ofsensors in an autonomous vehicle is received. A switch such as a timesensitive network switch may be configured to receive the sensor datafrom the array of sensors. Based on vehicle operation data, first sensordata from a first sensor group is prioritized over second sensor datafrom a second sensor group and the first data is transmitted by the timesensitive network switch for processing prior to the second data beingtransmitted for processing.

The vehicle operation data may include a transmission-gear of theautonomous vehicle such as Reverse or Drive and the vehicle operationdata may be received from a data bus (e.g. Controller Area Network bus)of the autonomous vehicle. If the transmission-gear of the autonomousvehicle is Reverse, sensors imaging the rear of the vehicle may beselected as the first sensor group and the first sensor data from therear-facing sensors may be prioritized over second sensor data fromother sensors. The first sensor data may be transmitted by the switch toprocessors that generate an external environment representation of theautonomous vehicle and prioritizing certain sensor data may increase thespeed that the autonomous vehicle can determine the more relevantobjects for navigation in its external environment. The externalenvironment representation may include mapping data and sensor data.

Vehicle operation data may also indicate a direction of the vehicle froman accelerometer or a plurality of readings from a GPS sensor includedin the autonomous vehicle. Based on the direction of the autonomousvehicle, sensor data from certain sensors in the array of sensors may beprioritized for transmission.

In a different example, the vehicle operation data may also indicate aspeed of the autonomous vehicle from a speedometer or a plurality ofreadings from a GPS sensor included in the autonomous vehicle. Based onthe speed of the autonomous vehicle, sensor data from certain sensors inthe array of sensors may be prioritized for transmission to processorsthat generate an external environment representation of the autonomousvehicle. These and other implementations will be discussed with respectto FIG. 1A-6 in greater detail below.

FIG. 1A illustrates an example autonomous vehicle 100 that includes anarray of sensors, in accordance with aspects of the disclosure. Theillustrated autonomous vehicle 100 includes an array of sensorsconfigured to capture one or more objects of an external environment ofthe autonomous vehicle and to generate sensor data related to thecaptured one or more objects for purposes of controlling the operationof autonomous vehicle 100. FIG. 1A shows sensor 133A, 133B, 133C, 133D,and 133E. FIG. 1B illustrates a top view of autonomous vehicle 100including sensors 133F, 133G, 133H, and 133I in addition to sensors133A, 133B, 133C, 133D, and 133E. FIG. 1C illustrates a block diagram199 of an example system for autonomous vehicle 100. For example,autonomous vehicle 100 may include powertrain 102 including prime mover104 powered by energy source 106 and capable of providing power todrivetrain 108. Autonomous vehicle 100 may further include controlsystem 110 that includes direction control 112, powertrain control 114,and brake control 116. Autonomous vehicle 100 may be implemented as anynumber of different vehicles, including vehicles capable of transportingpeople and/or cargo and capable of traveling in a variety of differentenvironments. It will be appreciated that the aforementioned components102 - 116 can vary widely based upon the type of vehicle within whichthese components are utilized.

The implementations discussed hereinafter, for example, will focus on awheeled land vehicle such as a car, van, truck, or bus. In suchimplementations, prime mover 104 may include one or more electric motorsand/or an internal combustion engine (among others). The energy sourcemay include, for example, a fuel system (e.g., providing gasoline,diesel, hydrogen), a battery system, solar panels or other renewableenergy source, and/or a fuel cell system. Drivetrain 108 may includewheels and/or tires along with a transmission and/or any othermechanical drive components suitable for converting the output of primemover 104 into vehicular motion, as well as one or more brakesconfigured to controllably stop or slow the autonomous vehicle 100 anddirection or steering components suitable for controlling the trajectoryof the autonomous vehicle 100 (e.g., a rack and pinion steering linkageenabling one or more wheels of autonomous vehicle 100 to pivot about agenerally vertical axis to vary an angle of the rotational planes of thewheels relative to the longitudinal axis of the vehicle). In someimplementations, combinations of powertrains and energy sources may beused (e.g., in the case of electric/gas hybrid vehicles). In someimplementations, multiple electric motors (e.g., dedicated to individualwheels or axles) may be used as a prime mover.

Direction control 112 may include one or more actuators and/or sensorsfor controlling and receiving feedback from the direction or steeringcomponents to enable the autonomous vehicle 100 to follow a desiredtrajectory. Powertrain control 114 may be configured to control theoutput of powertrain 102, e.g., to control the output power of primemover 104, to control a gear of a transmission in drivetrain 108,thereby controlling a speed and/or direction of the autonomous vehicle100. Brake control 116 may be configured to control one or more brakesthat slow or stop autonomous vehicle 100, e.g., disk or drum brakescoupled to the wheels of the vehicle.

Other vehicle types, including but not limited to off-road vehicles,all-terrain or tracked vehicles, or construction equipment willnecessarily utilize different powertrains, drivetrains, energy sources,direction controls, powertrain controls and brake controls, as will beappreciated by those of ordinary skill having the benefit of the instantdisclosure. Moreover, in some implementations some of the components canbe combined, e.g., where directional control of a vehicle is primarilyhandled by varying an output of one or more prime movers. Therefore,implementations disclosed herein are not limited to the particularapplication of the herein-described techniques in an autonomous wheeledland vehicle.

In the illustrated implementation, autonomous control over autonomousvehicle 100 is implemented in vehicle control system 120, which mayinclude one or more processors in processing logic 122 and one or morememories 124, with processing logic 122 configured to execute programcode (e.g. instructions 126) stored in memory 124. Processing logic 122may include graphics processing unit(s) (GPUs) and/or central processingunit(s) (CPUs), for example.

Sensors 133A-133I may include various sensors suitable for collectingdata from an autonomous vehicle’s surrounding environment for use incontrolling the operation of the autonomous vehicle. For example,sensors 133A-133I can include RADAR unit 134, LIDAR unit 136, 3Dpositioning sensor(s) 138, e.g., a satellite navigation system such asGPS, GLONASS, BeiDou, Galileo, or Compass. In some implementations, 3Dpositioning sensor(s) 138 can determine the location of the vehicle onthe Earth using satellite signals. Sensors 133A-133I can optionallyinclude one or more ultrasonic sensors, one or more cameras 140, and/oran Inertial Measurement Unit (IMU) 142. In some implementations, camera140 can be a monographic or stereographic camera and can record stilland/or video images. Camera 140 may include a ComplementaryMetal-Oxide-Semiconductor (CMOS) image sensor configured to captureimages of one or more objects in an external environment of autonomousvehicle 100. IMU 142 can include multiple gyroscopes and accelerometerscapable of detecting linear and rotational motion of autonomous vehicle100 in three directions. One or more encoders (not illustrated) such aswheel encoders may be used to monitor the rotation of one or more wheelsof autonomous vehicle 100.

The outputs of sensors 133A-133I may be provided to control subsystems150, including, localization subsystem 152, planning subsystem 156,perception subsystem 154, and control subsystem 158. Localizationsubsystem 152 is configured to determine the location and orientation(also sometimes referred to as the “pose”) of autonomous vehicle 100within its surrounding environment, and generally within a particulargeographic area. The location of an autonomous vehicle can be comparedwith the location of an additional vehicle in the same environment aspart of generating labeled autonomous vehicle data. Perception subsystem154 is configured to detect, track, classify, and/or determine objectswithin the environment surrounding autonomous vehicle 100. Planningsubsystem 156 is configured to generate a trajectory for autonomousvehicle 100 over a particular timeframe given a desired destination aswell as the static and moving objects within the environment. A machinelearning model in accordance with several implementations can beutilized in generating a vehicle trajectory. Control subsystem 158 isconfigured to operate control system 110 in order to implement thetrajectory of the autonomous vehicle 100. In some implementations, amachine learning model can be utilized to control an autonomous vehicleto implement the planned trajectory.

It will be appreciated that the collection of components illustrated inFIG. 1C for vehicle control system 120 is merely exemplary in nature.Individual sensors may be omitted in some implementations. In someimplementations, different types of sensors illustrated in FIG. 1C maybe used for redundancy and/or for covering different regions in anenvironment surrounding an autonomous vehicle. In some implementations,different types and/or combinations of control subsystems may be used.Further, while subsystems 152 — 158 are illustrated as being separatefrom processing logic 122 and memory 124, it will be appreciated that insome implementations, some or all of the functionality of subsystems 152— 158 may be implemented with program code such as instructions 126resident in memory 124 and executed by processing logic 122, and thatthese subsystems 152 — 158 may in some instances be implemented usingthe same processor(s) and/or memory. Subsystems in some implementationsmay be implemented at least in part using various dedicated circuitlogic, various processors, various field programmable gate arrays(“FPGA”), various application-specific integrated circuits (“ASIC”),various real time controllers, and the like, as noted above, multiplesubsystems may utilize circuitry, processors, sensors, and/or othercomponents. Further, the various components in vehicle control system120 may be networked in various manners.

In some implementations, autonomous vehicle 100 may also include asecondary vehicle control system (not illustrated), which may be used asa redundant or backup control system for autonomous vehicle 100. In someimplementations, the secondary vehicle control system may be capable ofoperating autonomous vehicle 100 in response to a particular event. Thesecondary vehicle control system may only have limited functionality inresponse to the particular event detected in primary vehicle controlsystem 120. In still other implementations, the secondary vehiclecontrol system may be omitted.

In some implementations, different architectures, including variouscombinations of software, hardware, circuit logic, sensors, and networksmay be used to implement the various components illustrated in FIG. 1C.Each processor may be implemented, for example, as a microprocessor andeach memory may represent the random access memory (“RAM”) devicescomprising a main storage, as well as any supplemental levels of memory,e.g., cache memories, non-volatile or backup memories (e.g.,programmable or flash memories), or read- only memories. In addition,each memory may be considered to include memory storage physicallylocated elsewhere in autonomous vehicle 100, e.g., any cache memory in aprocessor, as well as any storage capacity used as a virtual memory,e.g., as stored on a mass storage device or another computer controller.Processing logic 122 illustrated in FIG. 1C, or entirely separateprocessing logic, may be used to implement additional functionality inautonomous vehicle 100 outside of the purposes of autonomous control,e.g., to control entertainment systems, to operate doors, lights, orconvenience features.

In addition, for additional storage, autonomous vehicle 100 may alsoinclude one or more mass storage devices, e.g., a removable disk drive,a hard disk drive, a direct access storage device (“DASD”), an opticaldrive (e.g., a CD drive, a DVD drive), a solid state storage drive(“SSD”), network attached storage, a storage area network, and/or a tapedrive, among others. Furthermore, autonomous vehicle 100 may include auser interface 164 to enable autonomous vehicle 100 to receive a numberof inputs from a passenger and generate outputs for the passenger, e.g.,one or more displays, touchscreens, voice and/or gesture interfaces,buttons and other tactile controls. In some implementations, input fromthe passenger may be received through another computer or electronicdevice, e.g., through an app on a mobile device or through a webinterface.

In some implementations, autonomous vehicle 100 may include one or morenetwork interfaces, e.g., network interface 162, suitable forcommunicating with one or more networks 170 (e.g., a Local Area Network(“LAN”), a wide area network (“WAN”), a wireless network, and/or theInternet, among others) to permit the communication of information withother computers and electronic devices, including, for example, acentral service, such as a cloud service, from which autonomous vehicle100 receives environmental and other data for use in autonomous controlthereof. In some implementations, data collected by one or more sensors133A-133I can be uploaded to computing system 172 through network 170for additional processing. In such implementations, a time stamp can beassociated with each instance of vehicle data prior to uploading.

Processing logic 122 illustrated in FIG. 1C, as well as variousadditional controllers and subsystems disclosed herein, generallyoperates under the control of an operating system and executes orotherwise relies upon various computer software applications,components, programs, objects, modules, or data structures, as may bedescribed in greater detail below. Moreover, various applications,components, programs, objects, or modules may also execute on one ormore processors in another computer coupled to autonomous vehicle 100through network 170, e.g., in a distributed, cloud-based, orclient-server computing environment, whereby the processing required toimplement the functions of a computer program may be allocated tomultiple computers and/or services over a network.

Routines executed to implement the various implementations describedherein, whether implemented as part of an operating system or a specificapplication, component, program, object, module or sequence ofinstructions, or even a subset thereof, will be referred to herein as“program code.” Program code typically comprises one or moreinstructions that are resident at various times in various memory andstorage devices, and that, when read and executed by one or moreprocessors, perform the steps necessary to execute steps or elementsembodying the various aspects of the invention. Moreover, whileimplementations have and hereinafter may be described in the context offully functioning computers and systems, it will be appreciated that thevarious implementations described herein are capable of beingdistributed as a program product in a variety of forms, and thatimplementations can be implemented regardless of the particular type ofcomputer readable media used to actually carry out the distribution.Examples of computer readable media include tangible, non-transitorymedia such as volatile and non-volatile memory devices, floppy and otherremovable disks, solid state drives, hard disk drives, magnetic tape,and optical disks (e.g., CD-ROMs, DVDs) among others.

In addition, various program code described hereinafter may beidentified based upon the application within which it is implemented ina specific implementation. However, it should be appreciated that anyparticular program nomenclature that follows is used merely forconvenience, and thus the invention should not be limited to use solelyin any specific application identified and/or implied by suchnomenclature. Furthermore, given the typically endless number of mannersin which computer programs may be organized into routines, procedures,methods, modules, objects, and the like, as well as the various mannersin which program functionality may be allocated among various softwarelayers that are resident within a typical computer (e.g., operatingsystems, libraries, API’s, applications, applets), it should beappreciated that the invention is not limited to the specificorganization and allocation of program functionality described herein.

Those skilled in the art, having the benefit of the present disclosure,will recognize that the exemplary environment illustrated in FIG. 1C isnot intended to limit implementations disclosed herein. Indeed, thoseskilled in the art will recognize that other alternative hardware and/orsoftware environments may be used without departing from the scope ofimplementations disclosed herein.

FIG. 2 illustrates a block diagram of example system 200 that may beincluded in an autonomous vehicle, in accordance with aspects of thedisclosure. System 200 includes main processing logic 205, timesensitive network switch 250, power distribution module 270, vehiclebattery 285, network 290, camera array 261, RADAR sensor array 263, andLIDAR sensor array 265. Sensors in addition to camera array 261, RADARsensor array 263, and LIDAR sensor array 265 may also be included insystem 200. Vehicle battery 285 may be a main vehicle battery for avehicle such as autonomous vehicle 100 for operating the vehicleelectrical subsystems. Vehicle battery 285 may provide a voltage of12-14 VDC, for example. Vehicle battery 285 is configured to provideelectrical power to power distribution module 270 through batteryinterface 283, in FIG. 2 . Power distribution module 270 may beconfigured to convert the vehicle battery voltage provided by vehiclebattery 285 to an elevated voltage and provide the elevated voltage totime sensitive network switch 250 through elevated voltage interface273. Power distribution module 270 may include power converters and/orpower regulators (e.g. switching power supplies) configured to convertthe vehicle battery voltage to an elevated voltage.

In addition to receiving the elevated voltage from power distributionmodule 270, time sensitive network switch 250 is configured to send andreceive data. In autonomous vehicles, high-speed data transfer for datathat impacts vehicle operation is critical. Time sensitive networkswitch 250 is communicatively coupled to main processing logic 205through high-speed data interface 207. High-speed data interface 207 maybe one or more 510 Gigabit per second (Gb/s) connections. In animplementation, main processing logic 205 is communicatively coupled totime sensitive network switch 250 through two 10 Gb/s connections ofhigh-speed data interface 207.

Main processing logic 205 may be a processing board including aplurality of multi-core processors and a plurality of memory devices.The processing board may also include communication interfaces and becoupled to a heat-sink or be cooled by a fan system. Main processinglogic 205 may process the sensor data received from time sensitivenetwork switch 250 to determine objects in an external environment of anautonomous vehicle and operate the vehicle based at least in part on thedetermination. “Objects” may include inanimate objects such asobstacles, barriers, building, other vehicles, poles, and/or signs, forexample. Objects may, in some implementations, refer additionally toactors on the road such as pedestrians and bicyclists. In someimplementations, main processing logic 205 accesses mapping data 203 inaddition to processing the sensor data received from time sensitivenetwork switch 250 to determine operation instructions for operating theautonomous vehicle. Mapping data 203 may have been collected by vehiclesother than the vehicle that is collecting the sensor data. Mapping data203 may include positions of static bodies (e.g. buildings, barriers,streets) in an external environment of an autonomous vehicle. Mappingdata 203 may be provided to main processing logic 205 from network 290through interface 201. In some implementations, interface 201 is awireless protocol such as IEEE 802.11 protocols or cellular dataprotocols (e.g. 3G, 4G, LTE, 5G). Mapping data 203 may be updated by aplurality of vehicles and periodically or continually updated by mainprocessing logic 205 by downloading the updated mapping data fromnetwork 290.

In the illustrated implementation, main processing logic 205 maydetermine an operation instruction based at least in part on thereceived sensor data. Main processing logic 205 may then send thatoperation instruction to control system 210 by way of high-speed datainterface 207, time sensitive network switch 250, and control interface217. Control interface 217 is communicatively coupled between interface258 of time sensitive network switch 250 and control system 210.Interface 258 may include an input port and an output port. Controlinterface 217 may be one or more 10 Gb/s connections. Control system 210includes direction control 212, powertrain control 214, and brakecontrol 216, which may be configured similarly to direction control 112,powertrain control 114, and brake control 116 illustrated in FIG. 1C,respectively. Therefore, operation instructions generated by mainprocessing logic 205 may be generated based on mapping data 203 and thesensor data received from time sensitive network switch 250. Once mainprocessing logic 205 generates the operation instruction(s), theoperations instruction(s) may be sent to control system 210 through timesensitive network switch 250.

Time sensitive network switch 250 is individually coupled to a pluralityof sensors by way of a data-power interface, in FIG. 2 . In theparticular illustration of FIG. 2 , time sensitive network switch 250 isindividually coupled to each camera in camera array 261 throughdata-power interfaces 237A, 237B, and 237C. That is, each camera incamera array 261 has a connector (e.g. connectors 235A-235C) coupled toa connector (e.g. connectors 239A-239C) of time sensitive network switch250 through its own data-power interface (e.g. data-power interface237A-237C) . In the illustrated implementation of FIG. 2 , connector235A is coupled to connector 239A through data-power interface 237A,connector 237B is coupled to connector 239B through data-power interface237B, and connector 237C is coupled to connector 239C through data-powerinterface 237C. Similarly, time sensitive network switch 250 isindividually coupled to each RADAR sensor in RADAR sensor array 263through data-power interfaces 237G, 237H, and 237I. That is, each RADARsensor in RADAR sensor array 263 has a connector (e.g. connectors235G-235I) coupled to a connector (e.g. connectors 239G-239I) of timesensitive network switch 250 through its own data-power interface (e.g.data-power interface 237G-237I). In the illustrated implementation ofFIG. 2 , connector 235G is coupled to connector 239G through data-powerinterface 237G, connector 235H is coupled to connector 239H throughdata-power interface 237H, and connector 235I is coupled to connector239I through data-power interface 237I. FIG. 2 also illustrates thattime sensitive network switch 250 is individually coupled to each LIDARsensor in LIDAR sensor array 265 through data-power interfaces 237D,237E, and 237F. That is, each LIDAR sensor in LIDAR sensor array 265 hasa connector (e.g. connectors 235D-235F) coupled to a connector (e.g.connectors 239D-239F) of time sensitive network switch 250 through itsown data-power interface (e.g. data-power interface 237D-237F). In theillustrated implementation of FIG. 2 , connector 235D is coupled toconnector 239D through data-power interface 237D, connector 235E iscoupled to connector 239E through data-power interface 237E, andconnector 235F is coupled to connector 239F through data-power interface237F. In these implementations, the cameras, RADAR sensors, and LIDARsensor are merely examples of sensors that can be implemented as sensorsof an autonomous vehicle that may be coupled to time sensitive networkswitch 250 through a data-power interface (e.g., data-power interface237A-237I). Consequently, the data-power interface may separately coupleany sensors that are utilized in different implementations to timesensitive network switch 250 where time sensitive network switch 250includes a separate connector for the data-power interface of eachsensor in the array of sensors.

Data-power interfaces 237A-237I includes at least one high-speed vehiclecommunication link and may also provide an elevated voltage to eachsensor to power the sensor. The high-speed vehicle communication linkmay be defined as more than 100 Megabits per second (Mb/s), in someimplementations.

Time sensitive network switch 250 is configured to receive sensor datafrom any of the sensors in the array of sensors that are coupled to timesensitive network switch 250 through data-power interface 237. Timesensitive network switch 250 is “time sensitive” because it isconfigured to transfer the received sensor data to main processing logic205 with very little delay so that main processing logic 205 can utilizethe sensor data to operate the autonomous vehicle to be responsive toobjects that are sensed by the sensors. Time sensitive network switch250 may time-stamp received sensor data before forwarding the sensordata to main processing logic 205. Time sensitive network switch 250 mayinclude a plurality of multi-core processors. Time sensitive networkswitch 250 includes prioritization engine 253 to prioritize thetransmission of selected sensor data through interface 257, in FIG. 2 .For example, prioritization engine 253 may prioritize the transmissionof first sensor data from particular sensors over the transmission ofsecond sensor data from different sensor based on vehicle operation dataof the autonomous vehicle. In some implementations, one or moreprocessors that is external to a time sensitive switch may control thetime sensitive network switch to prioritize particular sensor data.

In some implementations, a time sensitive network switch can prioritizethe transmission of sensor data in multiple levels. For example, a timesensitive network switch can prioritize the transmission of sensor datafrom a first sensor group, then allow the transmission of sensor datafrom a second sensor group, and then allow the transmission of sensordata from a third sensor group.

In some implementations, a time sensitive network switch can prioritizethe transmission of sensor data within a group of sensors. For example,where an array of sensors includes multiple LIDAR sensors, a timesensitive network switch can prioritize the transmission of sensor datafrom a particular LIDAR sensor over transmission of sensor data fromLIDAR sensors other than the particular LIDAR sensor. In someimplementations, a time sensitive network switch can prioritize thetransmission of sensor data in multiple levels. For example, where anarray of sensors includes multiple LIDAR sensors, a time sensitivenetwork switch can prioritize the transmission of sensor data from afirst LIDAR sensor, then allow the transmission of sensor data from asecond LIDAR sensor, and then allow the transmission of sensor data froma third LIDAR sensor.

Interface 257 may include an input communication port and an outputcommunication port. The output communication port is configured totransmit sensor data such as first sensor data 271 and second sensordata 272 to main processing logic 205 and the input communication portis configured to receive data such as operation instructions 274 frommain processing logic 205.

FIG. 3 illustrates autonomous vehicle 300 navigating roadway 302, inaccordance with aspects of the disclosure. In one illustrative example,roadway 302 is a driveway or alley and autonomous vehicle 300 traversesin rearward direction 351. To travel in rearward direction 351,autonomous vehicle 300 may enter a reverse transmission state where thetransmission of the vehicle is in reverse. In the implementation of FIG.2 , transmission 215 of powertrain control 214 may be shifted intoreverse and vehicle operation data 275 including the reversetransmission state may be sent to prioritization engine 253 of timesensitive network switch 250 through control interface 217. The reversetransmission state may be digitally incorporated into a vehicleoperation data packet sent over a Controller Area Network (CAN) bus ofautonomous vehicle 300 that is also transmitted over control interface217 to time sensitive network switch 250. Vehicle operation data 275 isindicative of an operation state of an autonomous vehicle and is derivedfrom sensors included in autonomous vehicle 300 or data accessible fromwithin autonomous vehicle 300. Vehicle operation data 275 may include atransmission state of the vehicle (e.g. reverse or drive), a speed ofthe vehicle measured by the speedometer or derived from a GPS sensor ofthe vehicle, a direction of the vehicle derived from accelerometer ofGPS data, or otherwise.

When autonomous vehicle 300 is traversing in rearward direction 351,certain sensors in the array of sensors of autonomous vehicle 300 may bebetter positioned to detect or image bicycle 321 or pedestrian 323 andimaging the rear of the vehicle may have a higher priority. Hence, in animplementation, a first sensor group (e.g. rear sensors) may be selectedfrom an array of sensors based on vehicle operation data that includes areverse transmission state that indicates a transmission of the vehicleis shifted into reverse. Based on selecting the first sensor group (e.g.rear-facing sensors), time sensitive network switch 250 may prioritizethe transmission of the first sensor data from the first sensor groupover transmission of second sensor data from a second sensor group inthe array of sensors. The second sensor group may be the remainder ofthe non-selected sensors in the array of sensors, in someimplementations. For example, if the rear sensor(s) are the selectedfirst sensor group, the second sensor group may include front sensorsconfigured to detect or image the front of the vehicle and/or sidesensors configured to detect or image the sides of the vehicle.

Referring to FIG. 5 , sensors 533H and 533I may be considered “rearsensors.” Sensors 533B and 533G may also be considered “rear sensors,”in some implementations. Sensors 533C, 533D, 533E, and 533F may beconsidered “front sensors,” in some implementations. In oneimplementation, only sensors 533E and 533D are considered “frontsensors.” FIG. 5 illustrates sensors 533A-533I that provide sensor datato time sensitive network switch 550 may have differentfields-of-imaging 544A-544I depending on a position of the sensor inautonomous vehicle 500. Sensors 533A-533I are coupled to provide sensordata to time sensitive network switch 550. Time sensitive network switch550 may be configured similarly to time sensitive network switch 250.FIG. 5 illustrates a total of nine sensors 533A-533I included inautonomous vehicle 500, although more sensors or fewer sensors may beused in other systems. Sensor 533B may be best positioned to detect orimage objects proximate to the right-rear side of autonomous vehicle 500that are in field-of-imaging 544B of sensor 533B. Field-of-imaging 544Bof sensor 533B may be 180 degrees or more. Similarly, sensor 533D may bebest positioned to detect or image objects proximate to the right-frontside of autonomous vehicle 500 that are in field-of-imaging 544D ofsensor 533D. Sensor 533F may be best positioned to detect or imageobjects proximate to the left-front side of autonomous vehicle 500 thatare in field-of-imaging 544F of sensor 533F. Sensor 533H may be bestpositioned to detect or image objects proximate to the left-rear side ofautonomous vehicle 500 that are in field-of-imaging 544H of sensor 533H.Of course, sensors 533C, 533D, 533G, and 533I are also configured todetect or image objects in their field-of-imaging (not illustrated) andsensor 533A may have a 360 degree field-of-imaging when it is disposedon the top of autonomous vehicle 500. Accordingly, sensor 533A may beselected as a rear sensor or a front sensor when a field-of-imaging forsensor 533A includes the rear-ward area of autonomous vehicle 500 or thefrontside of autonomous vehicle 500, respectively.

Returning again to FIG. 3 , autonomous vehicle 300 may traverse inforward direction 352 on roadway 302. To travel in forward direction352, autonomous vehicle 300 may enter a forward-gear transmission statewhere the transmission of the vehicle is in drive. In the implementationof FIG. 2 , transmission 215 of powertrain control 214 may be shiftedinto drive and vehicle operation data 275 including the forward-geartransmission state may be sent to prioritization engine 253 of timesensitive network switch 250 through control interface 217. Theforward-gear transmission state may be digitally incorporated into avehicle operation data packet sent over a CAN bus of autonomous vehicle300 that is also transmitted over control interface 217 to timesensitive network switch 250.

When autonomous vehicle 300 is traversing in forward direction 352,sensors in the array of sensors of autonomous vehicle 300 may be betterpositioned to detect or image objects in front of autonomous vehicle300. Sensor data from those sensors may have a higher imaging priority.Hence, in an implementation, a first sensor group (e.g. front sensors)may be selected from an array of sensors based on vehicle operation datathat includes a forward-gear transmission state that indicates atransmission of the vehicle is shifted into drive. Based on selectingthe first sensor group (e.g. front sensors), time sensitive networkswitch 250 may prioritize the transmission of the first sensor data fromthe first sensor group over transmission of second sensor data from asecond sensor group in the array of sensors. The second sensor group maybe the remainder of the non-selected sensors in the array of sensors, insome implementations. For example, if the front sensor(s) are theselected first sensor group, the second sensor group may include rearsensors configured to detect or image the rear-ward area of the vehicleand/or side sensors configured to detect or image the sides of thevehicle.

In some implementations, one or more measurements from an accelerometerincluded in autonomous vehicle 300 is used to determine that autonomousvehicle 300 is traversing in rearward direction 351 or forward direction352. In another implementation, a plurality of readings from a GPSsensor included in autonomous vehicle 300 is used to determine thatautonomous vehicle 300 is traversing in rearward direction 351 orforward direction 352. Vehicle operation data 275 may include forwarddirection 352 or rearward direction 351 of autonomous vehicle 300derived from accelerometer or GPS sensor measurements and based on thedirection of the autonomous vehicle, sensor data from certain sensors inthe array of sensors may be prioritized for transmission.

FIG. 4 illustrates a flow chart with an example process 400 ofprioritizing sensor data based on vehicle operation data, in accordancewith aspects of the disclosure. The order in which some or all of theprocess blocks appear in process 400 should not be deemed limiting.Rather, one of ordinary skill in the art having the benefit of thepresent disclosure will understand that some of the process blocks maybe executed in a variety of orders not illustrated, or even in parallel.All or a portion of the process blocks illustrated in FIG. 4 may beperformed by time sensitive network switch 250, for example.

In process block 405, sensor data from an array of sensors is received.The sensors in the array of sensors are configured to capture one ormore objects of an external environment of an autonomous vehicle bygenerating the sensor data (e.g. an image) of the captured one or moreobjects. Any of sensors 133A-133I in FIG. 1B or sensors 533A-533I inFIG. 5 may be in the array of sensors, for example.

In process block 410, vehicle operation data representative of a vehiclestate of the autonomous vehicle is received. The vehicle state indicatesa transmission gear (e.g. drive or reverse) of a transmission of theautonomous vehicle, in some implementations. The vehicle operation dataindicates a speed of the autonomous vehicle, in some implementations. Insome implementations, the vehicle operation data indicates a directionof travel of the autonomous vehicle. The vehicle operation data may bereceived from a vehicle data bus (e.g. CAN bus) of the autonomousvehicle.

In process block 415, a first sensor group is selected from the array ofsensors of the autonomous vehicle based on the vehicle operation data.The first sensor group may be a single sensor. When the vehicleoperation data indicates a rearward direction, rear-facing sensors maybe selected in the first sensor group. When vehicle operation dataindicates a forward direction, front-facing sensors may be selected inthe first sensor group.

In process block 420, transmission of first data generated by the firstsensor group is prioritized by a switch based on selecting the firstsensor group. Transmission of the first data is prioritized, by theswitch, over transmission of second sensor data generated by a secondsensor group in the array of sensors. In FIG. 2 , first sensor data 271may be sent to main processing logic 205 prior to second sensor data272, even when the first sensor data and the second sensor data arereceived by time sensitive network switch 250 at approximately the sametime, for example. Main processing logic 205 may generate an externalenvironment representation of the autonomous vehicle with the firstsensor data. The external environment representation may include mappingdata and sensor data. In some implementations, a switch that does nothave all the characteristics of time sensitive network switch 250 may beutilized in place of a time sensitive network switch. For example, aswitch may be utilized that does not time-stamp received sensor data.Utilizing a time sensitive network switch may assist in transferringsensor data with very little delay so that the sensor data can beutilized to operate the autonomous vehicle to be responsive to objectsthat are detected by the sensors. A time sensitive network switch maytime-stamp received sensor data before transferring the sensor data sothat processing logic that assists in operating the autonomous vehicleis able to synthesize sensor data that was detected during a same timeperiod.

Previous sensor data and mapping data may also be utilized in generatingthe external environment representation. In one implementation ofprocess 400, an updated external environment representation of theautonomous vehicle is generated with the second sensor data and theupdated external environment representation of the autonomous vehicle isgenerated subsequently to the external environment representation. Theexternal environment representation and the updated external environmentrepresentation may be utilized by planning subsystem 156 of FIG. 1C forplanning a trajectory for an autonomous vehicle while avoiding thestatic and moving objects within the external environment of theautonomous vehicle, for example. Control subsystem 158 may sendoperation instruction to control system 110 based on the plannedtrajectory determined by planning subsystem 156. When planning subsystem156 is executed at least in part by main processing logic 205 of FIG. 2, operation instructions 274 may be sent to control system 210 throughhigh-speed data interface 207, time sensitive network switch 250, andcontrol interface 217. Control system 210 may then apply the operationinstructions to control the autonomous vehicle.

In one implementation of process 400, the transmission of the firstsensor data and the second sensor data is from time sensitive networkswitch 250 to main processing logic 205 of the autonomous vehicle andtime sensitive network switch 250 is configured to receive the firstsensor data and the second sensor data from the array of sensors.

In one implementation of process 400, the array of sensors includes rearsensors disposed to detect or image a rear-ward area of the autonomousvehicle and front sensors disposed to detect or image a frontside areaof the autonomous vehicle and the vehicle operation data indicates arear-ward direction of the autonomous vehicle. In this implementation,the first sensor data (prioritized in transmission) may be generated bythe rear sensors and the second sensor data is generated by the frontsensors.

In one implementation of process 400, the array of sensors includes rearsensors disposed to detect or image a rear-ward area of the autonomousvehicle and front sensors disposed to detect or image a frontside areaof the autonomous vehicle and the vehicle operation data indicates aforward direction of the autonomous vehicle. In this implementation, thefirst sensor data (prioritized in transmission) is generated by thefront sensors and the second sensor data is generated by the rearsensors.

When first sensor data is being prioritized over second sensor data (bytime sensitive network switch 250 for example), an external environmentrepresentation of the autonomous vehicle may be generated withoutnecessarily waiting for the benefit of the second sensor data to updatethe external environment representation. Thus, in accordance withprocess 400 and aspects of this disclosure, main processing logic 205may be updated at a faster rate with potentially the most useful of thesensor data to generate and regenerate external environmentrepresentations of the autonomous vehicle that include static and movingobjects.

FIG. 6 illustrates autonomous vehicle 600 traveling in a forwarddirection 652 on roadway 602, in accordance with aspects of thedisclosure. In one implementation, sensor data from particular sensorsare prioritized based on a speed of autonomous vehicle 600 included inthe vehicle operation data. The speed of the vehicle may be receiveddigitally from the speedometer of the vehicle or derived from a seriesof GPS measurements, for example. When autonomous vehicle 600 istravelling at highway speeds, the front sensors may be selected andfirst sensor data from the front sensors may be prioritized by timesensitive network switch 250 for transmission to main processing logic205. In an implementation, the sensors selected as the first sensorgroup may be based on a modality of the sensors (e.g. image sensor,LIDAR, RADAR, ultrasonic) based on a speed of the vehicle included inthe vehicle operation data. Additionally, certain sensors may beconfigured for near-field or far-field imaging such as image sensorshaving lenses of different focal lengths. Other sensors of the same typemay also be configured for near-field or far-field imaging based on thewavelength or intensity of illumination light or the frequency or beamshape of transmitted radio waves. Therefore, for any of these abovereasons, certain sensor data generated by different sensors may beprioritized, in transmission, based on a speed of the vehicle, inaccordance with implementations of the disclosure.

The term “processing logic” (e.g. main processing logic 205 orprocessing logic 122) in this disclosure may include one or moreprocessors, microprocessors, multi-core processors, and/or FieldProgrammable Gate Arrays (FPGAs) to execute operations disclosed herein.In some implementations, memories (not illustrated) are integrated intothe processing logic to store instructions to execute operations and/orstore data. Processing logic may include analog or digital circuitry toperform the operations disclosed herein.

Network 170 and/or 290 may include any network or network system suchas, but not limited to, the following: a peer-to-peer network; a LocalArea Network (LAN); a Wide Area Network (WAN); a public network, such asthe Internet; a private network; a cellular network; a wireless network;a wired network; a wireless and wired combination network; and asatellite network.

The processes explained above are described in terms of computersoftware and hardware. The techniques described may constitutemachine-executable instructions embodied within a tangible ornon-transitory machine (e.g., computer) readable storage medium, thatwhen executed by a machine will cause the machine to perform theoperations described. Additionally, the processes may be embodied withinhardware, such as an application specific integrated circuit (“ASIC”) orotherwise.

A tangible non-transitory machine-readable storage medium includes anymechanism that provides (i.e., stores) information in a form accessibleby a machine (e.g., a computer, network device, personal digitalassistant, manufacturing tool, any device with a set of one or moreprocessors). For example, a machine-readable storage medium includesrecordable/non-recordable media (e.g., read only memory (ROM), randomaccess memory (RAM), magnetic disk storage media, optical storage media,flash memory devices).

The above description of illustrated implementations of the invention,including what is described in the Abstract, is not intended to beexhaustive or to limit the invention to the precise forms disclosed.While specific implementations of, and examples for, the invention aredescribed herein for illustrative purposes, various modifications arepossible within the scope of the invention, as those skilled in therelevant art will recognize.

These modifications can be made to the invention in light of the abovedetailed description. The terms used in the following claims should notbe construed to limit the invention to the specific implementationsdisclosed in the specification. Rather, the scope of the invention is tobe determined entirely by the following claims, which are to beconstrued in accordance with established doctrines of claiminterpretation.

What is claimed is:
 1. An autonomous vehicle comprising: a controlsystem configured to control the autonomous vehicle based on operationinstructions; an array of sensors configured to generate sensor datarelated to one or more objects in an external environment, wherein thearray of sensors includes a first sensor group configured to generatefirst sensor data and a second sensor group configured to generatesecond sensor data; processing logic configured to generate theoperation instructions based on the sensor data; and a switch coupledbetween the array of sensors and the processing logic to buffer theprocessing logic from the sensor data, wherein the switch is furthercoupled between the processing logic and the control system to providethe operation instructions from the processing logic to the controlsystem, and wherein the switch includes: a prioritization engineconfigured to prioritize an order of transmission, from the switch tothe processing logic, of the first sensor data over the second sensordata based on vehicle operation data received by the prioritizationengine.
 2. The autonomous vehicle of claim 1, wherein one of the firstsensor group and the second sensor group includes rear sensors disposedto detect a rear-ward area of the autonomous vehicle and wherein theother of the first sensor group and the second sensor group includesfront sensors disposed to detect a frontside area of the autonomousvehicle.
 3. The autonomous vehicle of claim 2, wherein the first sensordata is generated by the rear sensors and the second sensor data isgenerated by the front sensors.
 4. The autonomous vehicle of claim 2,wherein the first sensor data is generated by the front sensors and thesecond sensor data is generated by the rear sensors.
 5. The autonomousvehicle of claim 2, wherein the switch is configured to receive thevehicle operation data from a vehicle bus of the autonomous vehicle, andwherein the vehicle operation data includes at least one of aforward-gear transmission state or a reverse transmission state.
 6. Theautonomous vehicle of claim 1, wherein the vehicle operation dataincludes a speed of the autonomous vehicle.
 7. The autonomous vehicle ofclaim 1, wherein the array of sensors includes at least one of a LIDARsensor, an ultrasonic sensor, a camera, or a RADAR sensor.
 8. A systemfor an autonomous vehicle, the system comprising: a control systemconfigured to control the autonomous vehicle based on operationinstructions; processing logic configured to generate the operationinstructions based on first sensor data obtained by a first sensor groupand second sensor data obtained by a second sensor group, wherein thefirst sensor data and the second sensor data are representative of oneor more objects in an external environment of the autonomous vehicle;and a switch coupled to the control system and the processing logic, andconfigured to receive the first sensor data and the second sensor data,wherein the switch is further configured to buffer the processing logicfrom the first sensor data and the second sensor data, wherein theswitch is further configured to provide the operation instructions fromthe processing logic to the control system, and wherein the switchincludes: a prioritization engine configured to prioritize an order oftransmission, from the switch to the processing logic, of the firstsensor data over the second sensor data based on vehicle operation datareceived by the prioritization engine.
 9. The system of claim 8, whereinone of the first sensor group and the second sensor group includes rearsensors disposed to detect a rear-ward area of the autonomous vehicleand wherein the other of the first sensor group and the second sensorgroup includes front sensors disposed to detect a frontside area of theautonomous vehicle.
 10. The system of claim 9, wherein the first sensordata is generated by the rear sensors and the second sensor data isgenerated by the front sensors.
 11. The system of claim 9, wherein thefirst sensor data is generated by the front sensors and the secondsensor data is generated by the rear sensors.
 12. The system of claim 9,wherein the switch is configured to receive the vehicle operation datafrom a vehicle bus of the autonomous vehicle, and wherein the vehicleoperation data includes at least one of a forward-gear transmissionstate or a reverse transmission state.
 13. The system of claim 8,wherein the vehicle operation data includes a speed of the autonomousvehicle.
 14. The system of claim 8, wherein at least one of the firstsensor group or the second sensor group includes a LIDAR sensor, anultrasonic sensor, a camera, or a RADAR sensor.
 15. A switch system foran autonomous vehicle, the switch system comprising: a first interfaceto be coupled to a control system of the autonomous vehicle, wherein thecontrol system is configured to control the autonomous vehicle based onoperation instructions; a second interface to be coupled to a processinglogic of the autonomous vehicle, wherein the processing logic isconfigured to generate operation instructions based on first sensor dataand second sensor data that is representative of one or more objects inan external environment of the autonomous vehicle; and a plurality ofconnectors to be coupled to a first sensor group and a second sensorgroup, wherein the first sensor group and the second sensor group areconfigured to generate the first sensor data and the second sensor data,respectively, wherein the switch system is configured to: receive thefirst sensor data and the second sensor data via the plurality ofconnectors and provide the first sensor data and the second sensor datato the processing logic via the second interface, receive the operationinstructions via the second interface and provide the operationinstructions to the control system via the first interface, andprioritize an order of transmission, to the processing logic via thesecond interface, of the first sensor data over the second sensor databased on vehicle operation data received by the switch system.
 16. Theswitch system of claim 15, wherein one of the first sensor group and thesecond sensor group includes rear sensors configured to detect arear-ward area of the autonomous vehicle and wherein the other of thefirst sensor group and the second sensor group includes front sensorsconfigured to detect a frontside area of the autonomous vehicle.
 17. Theswitch system of claim 16, wherein the first sensor data is generated bythe rear sensors and the second sensor data is generated by the frontsensors.
 18. The switch system of claim 16, wherein the first sensordata is generated by the front sensors and the second sensor data isgenerated by the rear sensors.
 19. The switch system of claim 15,wherein the switch system is further configured to receive the vehicleoperation data from a vehicle bus of the autonomous vehicle, and whereinthe vehicle operation data includes at least one of a forward-geartransmission state or a reverse transmission state.
 20. The switchsystem of claim 15, wherein at least one of the first sensor group orthe second sensor group includes a LIDAR sensor, an ultrasonic sensor, acamera, or a RADAR sensor.